Title page for etd-0818110-113700


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URN etd-0818110-113700
Author Chien-Hung Chen
Author's Email Address No Public.
Statistics This thesis had been viewed 5334 times. Download 1297 times.
Department Information Management
Year 2009
Semester 2
Degree Master
Type of Document
Language English
Title Using Trust for Recommendation by Differentiating Users and Products
Date of Defense 2010-06-29
Page Count 47
Keyword
  • User bias
  • Product Controversy
  • Trust Network
  • Recommender System
  • E-commerce
  • Abstract Living in the information-overloading age, it is difficult to find the right information and
    identify the resources they need on the websites. As to a user, it is time-consuming in browsing,
    searching, and making a decision to buy products on online stores. Therefore, many
    E-commerce websites have implemented recommender systems that intend to provide users
    with professional recommendation for various types of products and services. Although many
    recommendation methods have been proposed, there are still some problems like the sparsity
    and the cold start problems. In addition, some researchers observe there exist users who are
    biased and products that are controversial. We conjecture that ratings given by biased users or
    given to controversial products may have impact on estimation accuracy of recommendation. In
    this thesis, we will examine the measures for user bias and product controversy and propose
    trust-based-recommendation techniques that take them into account. We evaluate the proposed
    techniques using the web of trust and rating data collected from the Epinions.com website. It is
    found that properly setting some parameters, the proposed trust network-based method that
    incorporates user bias achieve higher recommendation accuracy.
    Advisory Committee
  • Fu-Ren Lin - chair
  • Wang-Sho Yang - co-chair
  • San-Yih Hwang - advisor
  • Files
  • etd-0818110-113700.pdf
  • indicate accessible in a year
    Date of Submission 2010-08-18

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